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一个多层次的任务框架,用于事件序列分析

Kazi Tasnim Zinat, Saimadhav Naga Sakhamuri, Aaron Sun Chen

IEEE transactions on visualization and computer graphics

|September 18, 2024

概括

本研究引入了事件序列视觉分析的新任务框架,使得结果可以更好地在各个领域进行比较和转移. 拟议的多级框架解决了现有的事件序列数据分析抽象的局限性.

科学领域:

信息可视化信息可视化
人与计算机的交互
数据科学数据科学数据科学

背景情况:

事件序列数据的视觉分析工具是域特定的,阻碍了跨域的比较和可转移性.
现有的可视化任务抽象对于事件序列分析是不够的,经常忽视自动化技术.

研究的目的:

为事件序列分析提出一个无关域的,多层次的任务框架.
解决事件序列数据的视觉分析中当前任务抽象的局限性.

主要方法:

分析了58篇论文,介绍了事件序列可视化系统.
制定了一个四级框架:目标,意图,战略和技术.
定义的意图 (增加,简化,配置数据/可视化,管理来源) 和相关的策略和技术.

主要成果:

拟议的框架提供了一种结构化的方法来理解和分类事件序列视觉分析中的任务.
通过案例研究证明了框架的描述能力.
每种技术都可以用行动-输入-输出-标准四重奏来表达.

结论:

新的框架有助于更深入地理解和系统地比较事件序列视觉分析方法.
为为事件序列数据开发更通用和可转移的视觉分析工具提供了基础.

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